Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This article situates current deep learning (DL) artificial intelligence (AI) within Leroi-Gourhan’s deep history of the human species’ relation to technology. According to Leroi-Gourhan, technology is both a key element of anthropogenesis and a source of later tensions (or disentanglement) between the human species and its external and increasingly autonomous technics. Human organic (life-oriented) intelligence at first extends itself through technical (machine-oriented) intelligence, only to be later left behind by it. We propose a concept of machine intelligence that goes beyond technical intelligence, the latter a (still) hybrid human–machine intelligence. This new, emerging machine intelligence is DL AI. DL AI developed out of the failure of symbolic AI to instantiate a key generic component of intelligence: creativity. While symbolic AI was rigid and pre-programmed, DL is flexible and unpredictable, presenting an embryonic form of actual machine intelligence. Its creativity can be likened to the ancient Greek concept of metis, a cunning and polymorphous form of intelligence. Although often biased and problematic, DL exhibits a machine creativity that goes beyond the anthropocentric imaginings of AI as a (mechanistic) imitation of the human norm.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it